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From Frank Wang <>
Subject Re: Implementation for Linear Regression
Date Thu, 21 Oct 2010 03:15:24 GMT
Hi Ted,

thanks for your reply.
I'm trying a new model where I want to estimate the output as a timespan
quantified in number of seconds, which is not bounded. That's why I think
I'd use linear regression instead of logistic regression. (lemme know if i'm

I started on the code yesterday. The new AbstractOnlineLinearRegression
class is implementing the OnlineLearner interface. I updated the classify()
function to use linear model. I tried to follow the format for

I think since linear regression can be implemented w/ sgd, the train()
and regularize() functions would look similar. I'm not sure if i'm on the
right path. Any advice would be helpful.


On Wed, Oct 20, 2010 at 3:34 PM, Ted Dunning <> wrote:

> Frank,
> Sorry I didn't answer your previous email regarding this.
> It sounded to me like your application would actually be happier with a
> form
> of logistic regression.
> Perhaps we should talk some more about this on the list.
> If you want a normal linear regression, the current OnlineLearner interface
> isn't terribly appropriate since it assumes a 1 of n vector target
> variable.
> If you were to extend that interface to accept a vector form of target
> variable then linear regression would work (and some clever tricks would
> become possible for logistic regression).
> On Wed, Oct 20, 2010 at 1:57 PM, Frank Wang <> wrote:
> > Hi,
> >
> > I'm interested in implementing Linear Regression in Mahout. Who would be
> > the
> > point person for the algorithm? I'd love to discuss the implementation
> > details, or to help out if anyone is working on it already :)
> >
> > Thanks
> >

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